Iterative projection algorithms for solving constraint satisfaction problems: Effect of constraint convexity
2019 International Conference on Image and Vision Computing New Zealand (IVCNZ)(2019)
摘要
Many inverse problems in imaging involve solving an optimization problem. In many cases, the problem is high-dimensional and non-convex, requiring the solution of a difficult, non-convex, global optimization problem. Such problems can be made tractable by enforcing hard constraints and treating the problem as a constraint satisfaction problem to locate a global solution, which can be refined using soft constraints if necessary. Iterative projection algorithms are an effective way of solving non-convex constraint satisfaction problems. The difficulty of solution, and the performance of these algorithms, depends on the degree of non-convexity of the constraints. Here we use simulations of a phase retrieval problem to study the performance of an iterative projection algorithm, the difference map algorithm, to study performance as a function of non-convexity.
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关键词
Iterative projection algorithms,constraint satisfaction,phase retrieval,inverse problems,optimization
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